An efficient pointlstm for point clouds based gesture recognition
Point clouds contain rich spatial information, which provides complementary cues for
gesture recognition. In this paper, we formulate gesture recognition as an irregular …
gesture recognition. In this paper, we formulate gesture recognition as an irregular …
Caspr: Learning canonical spatiotemporal point cloud representations
We propose CaSPR, a method to learn object-centric Canonical Spatiotemporal Point Cloud
Representations of dynamically moving or evolving objects. Our goal is to enable …
Representations of dynamically moving or evolving objects. Our goal is to enable …
Imdiffusion: Imputed diffusion models for multivariate time series anomaly detection
Anomaly detection in multivariate time series data is of paramount importance for ensuring
the efficient operation of large-scale systems across diverse domains. However, accurately …
the efficient operation of large-scale systems across diverse domains. However, accurately …
Root cause analysis for microservice systems via hierarchical reinforcement learning from human feedback
In microservice systems, the identification of root causes of anomalies is imperative for
service reliability and business impact. This process is typically divided into two phases:(i) …
service reliability and business impact. This process is typically divided into two phases:(i) …
Xpert: Empowering incident management with query recommendations via large language models
Large-scale cloud systems play a pivotal role in modern IT infrastructure. However, incidents
occurring within these systems can lead to service disruptions and adversely affect user …
occurring within these systems can lead to service disruptions and adversely affect user …
TraceDiag: Adaptive, Interpretable, and Efficient Root Cause Analysis on Large-Scale Microservice Systems
Root Cause Analysis (RCA) is becoming increasingly crucial for ensuring the reliability of
microservice systems. However, performing RCA on modern microservice systems can be …
microservice systems. However, performing RCA on modern microservice systems can be …
Lidar-based 4d occupancy completion and forecasting
Scene completion and forecasting are two popular perception problems in research for
mobile agents like autonomous vehicles. Existing approaches treat the two problems in …
mobile agents like autonomous vehicles. Existing approaches treat the two problems in …
Learning scene dynamics from point cloud sequences
Understanding 3D scenes is a critical prerequisite for autonomous agents. Recently, LiDAR
and other sensors have made large amounts of data available in the form of temporal …
and other sensors have made large amounts of data available in the form of temporal …
A deep learning benchmark for first break detection from hardrock seismic reflection data
Deep learning techniques are used to tackle a variety of tasks related to seismic data
processing and interpretation. Although many works have shown the benefits of deep …
processing and interpretation. Although many works have shown the benefits of deep …
Quickskill: Novice skill estimation in online multiplayer games
Matchmaking systems are vital for creating fair matches in online multiplayer games, which
directly affects players' satisfactions and game experience. Most of the matchmaking …
directly affects players' satisfactions and game experience. Most of the matchmaking …